8x Faster Than ONNX Runtime: Zero-Allocation AI Inference in Pure C#
The article challenges the common belief that C# is too slow for high-performance AI. It introduces Overfit, an inference engine that outperforms ONNX Runtime by 800% in micro-inference tasks.
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Why it matters
This work challenges the common perception that C# is unsuitable for high-performance AI, and demonstrates the potential for .NET to deliver ultra-low latency inference.
Key Points
- 1Overfit leverages .NET 10, AVX-512 instructions, and zero-allocation patterns to achieve ultra-low latency inference
- 2Overfit completes 8 predictions in the time it takes ONNX Runtime to complete 1, with zero bytes allocated on the heap
- 3Overfit uses persistent inference buffers to eliminate Garbage Collector pauses, a major source of tail latency in .NET
- 4Overfit utilizes SIMD and AVX-512 instructions to process 16 float numbers in a single CPU instruction
Details
The article starts by addressing the common myth that
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